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  2. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    Round-to-nearest: () is set to the nearest floating-point number to . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used.

  3. Guard digit - Wikipedia

    en.wikipedia.org/wiki/Guard_digit

    Here, the product notation indicates a binary floating point representation with the exponent of the representation given as a power of two and with the significand given with three bits after the binary point. To compute the subtraction it is necessary to change the forms of these numbers so that they have the same exponent, and so that when ...

  4. decimal32 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal32_floating-point...

    Like the binary16 and binary32 formats, decimal32 uses less space than the actually most common format binary64.. In contrast to the binaryxxx data formats the decimalxxx formats provide exact representation of decimal fractions, exact calculations with them and enable human common 'ties away from zero' rounding (in some range, to some precision, to some degree).

  5. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    This alternative definition is significantly more widespread: machine epsilon is the difference between 1 and the next larger floating point number.This definition is used in language constants in Ada, C, C++, Fortran, MATLAB, Mathematica, Octave, Pascal, Python and Rust etc., and defined in textbooks like «Numerical Recipes» by Press et al.

  6. Multiply–accumulate operation - Wikipedia

    en.wikipedia.org/wiki/Multiply–accumulate...

    The MAC operation modifies an accumulator a: + When done with floating-point numbers, it might be performed with two roundings (typical in many DSPs), or with a single rounding. When performed with a single rounding, it is called a fused multiply–add (FMA) or fused multiply–accumulate (FMAC).

  7. IEEE 754-2008 revision - Wikipedia

    en.wikipedia.org/wiki/IEEE_754-2008_revision

    Annex "Z" introduced optional data types for supporting other fixed-width floating-point formats, as well as arbitrary-precision formats (i.e., where the precision of representation and rounding is determined at execution time) – some of this material was moved into the body of the draft by generalizing section 5.

  8. Single-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Single-precision_floating...

    A floating-point variable can represent a wider range of numbers than a fixed-point variable of the same bit width at the cost of precision. A signed 32-bit integer variable has a maximum value of 2 31 − 1 = 2,147,483,647, whereas an IEEE 754 32-bit base-2 floating-point variable has a maximum value of (2 − 2 −23) × 2 127 ≈ 3.4028235 ...

  9. Unum (number format) - Wikipedia

    en.wikipedia.org/wiki/Unum_(number_format)

    PERCIVAL is the first work that integrates the complete posit ISA and quire in hardware. It allows the native execution of posit instructions as well as the standard floating-point ones simultaneously. LibPosit. Chris Lomont. Single file C# MIT Licensed Any size No Extensive; no known bugs

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